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IJCAI
2007
13 years 9 months ago
The Value of Observation for Monitoring Dynamic Systems
We consider the fundamental problem of monitoring (i.e. tracking) the belief state in a dynamic system, when the model is only approximately correct and when the initial belief st...
Eyal Even-Dar, Sham M. Kakade, Yishay Mansour
NIPS
2004
13 years 9 months ago
VDCBPI: an Approximate Scalable Algorithm for Large POMDPs
Existing algorithms for discrete partially observable Markov decision processes can at best solve problems of a few thousand states due to two important sources of intractability:...
Pascal Poupart, Craig Boutilier
IAT
2005
IEEE
14 years 1 months ago
Decomposing Large-Scale POMDP Via Belief State Analysis
Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
Xin Li, William K. Cheung, Jiming Liu
GLOBECOM
2007
IEEE
13 years 11 months ago
Bursty Traffic in Energy-Constrained Opportunistic Spectrum Access
We design opportunistic spectrum access strategies for improving spectrum efficiency. In each slot, a secondary user chooses a subset of channels to sense and decides whether to ac...
Yunxia Chen, Qing Zhao, Ananthram Swami
IROS
2006
IEEE
121views Robotics» more  IROS 2006»
14 years 1 months ago
Planning and Acting in Uncertain Environments using Probabilistic Inference
— An important problem in robotics is planning and selecting actions for goal-directed behavior in noisy uncertain environments. The problem is typically addressed within the fra...
Deepak Verma, Rajesh P. N. Rao